Technology Training in Speech-Language Pathology: A Focus on Tablets and Apps Use of tablet computers has become ubiquitous in speech-language pathology assessment and intervention. With hundreds of applications of variable quality available, clinical training programs have the added responsibility of teaching students systematic, critical-thought-driven approaches to technology selection and evaluation. The purpose of this article is two-pronged: (1) we describe a ... Article
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Article  |   August 07, 2017
Technology Training in Speech-Language Pathology: A Focus on Tablets and Apps
Author Affiliations & Notes
  • Jeffrey Edwards
    California State University, East Bay, Hayward, CA
  • Elena Dukhovny
    California State University, East Bay, Hayward, CA
  • Disclosures
    Disclosures ×
  • Financial: This project was funded by a grant obtained by the author from the Center for Student Research when a graduate student at California State University, East Bay. At the time of this study, Jeffrey Edwards was receiving an hourly salary in his position as Coordinator for the Assistive Technology Lab in the Norma S. and Ray. R. Rees Speech, Language, and Hearing Clinic. Elena Dukhovny receives a full-time salary as an Assistant Professor in the Department of Communicative Sciences and Disorders at California State University, East Bay. She also serves as the faculty director for the Assistive Technology Lab in the Norma S. and Ray R. Rees Speech, Language, and Hearing Clinic.
    Financial: This project was funded by a grant obtained by the author from the Center for Student Research when a graduate student at California State University, East Bay. At the time of this study, Jeffrey Edwards was receiving an hourly salary in his position as Coordinator for the Assistive Technology Lab in the Norma S. and Ray. R. Rees Speech, Language, and Hearing Clinic. Elena Dukhovny receives a full-time salary as an Assistant Professor in the Department of Communicative Sciences and Disorders at California State University, East Bay. She also serves as the faculty director for the Assistive Technology Lab in the Norma S. and Ray R. Rees Speech, Language, and Hearing Clinic.×
  • Nonfinancial: Jeffrey Edwards and Elena Dukhovny have no relevant nonfinancial interests to disclose.
    Nonfinancial: Jeffrey Edwards and Elena Dukhovny have no relevant nonfinancial interests to disclose.×
Article Information
Speech, Voice & Prosodic Disorders / Professional Issues & Training / Telepractice & Computer-Based Approaches / Part 1
Article   |   August 07, 2017
Technology Training in Speech-Language Pathology: A Focus on Tablets and Apps
Perspectives of the ASHA Special Interest Groups, August 2017, Vol. 2, 33-48. doi:10.1044/persp2.SIG10.33
History: Received February 26, 2017 , Revised July 4, 2017 , Accepted July 7, 2017
Perspectives of the ASHA Special Interest Groups, August 2017, Vol. 2, 33-48. doi:10.1044/persp2.SIG10.33
History: Received February 26, 2017; Revised July 4, 2017; Accepted July 7, 2017

Use of tablet computers has become ubiquitous in speech-language pathology assessment and intervention. With hundreds of applications of variable quality available, clinical training programs have the added responsibility of teaching students systematic, critical-thought-driven approaches to technology selection and evaluation. The purpose of this article is two-pronged: (1) we describe a systematic approach to tablet/app implementation piloted within the Norma S. and Ray R. Rees Speech, Language, and Hearing Clinic at California State University, East Bay and, (2) we present the results of a survey that identifies current practices in app selection in other university clinics.

Background
The use of iPads and other tablet computers in speech-language pathology has become commonplace, with hundreds of applications (apps) available across areas of communicative disorders. As early as 2012, at least half of speech-language pathologists reported using iPads in clinical practice (Bruno-Dowling, 2012). There are many advantages to using mobile technologies in assessment and intervention, including client motivation, streamlined data-capturing, potential cost savings compared to printed materials, and the particular intervention advantages of visual, dynamic, and interactive presentation (e.g., interactive visual schedules for clients with autism-spectrum disorder; Gosnell, Costello, & Shane, 2011; Kearney & Maher, 2013). Disadvantages of app use include unclear paths to generalization; potentially distracting features, such as excessive animation or sound effects and activities that are motivating, but not therapeutic; as well as an overarching risk of placing the implementation of the technology before the needs of the client. As with any new technology, there is a need to strike a balance between being open to implementing useful new intervention tools and recognizing their limitations.
Growth of tablet-based computing in the early 2000s, and especially the 2010 release of Apple's iPad, was a game changer in tablet computing. Still, limited information has been available on the most effective ways for clinicians to select and implement iPad-supported interventions (e.g., Scherz, Dutton, Steiner, & Trost, 2010; Stone-MacDonald, 2015). Therefore, clinicians typically make tablet and app purchase decisions based on pragmatic factors such as word-of-mouth, marketing offers, lay user reviews, and cost. To align with the move towards evidence-based intervention in communicative sciences and disorders (Bernstein Ratner, 2006; Finn, 2011), we need to consider systematic approaches to technology selection and use. In addition, speech-language pathology training programs have the responsibility of modeling and teaching these critical technology-related skills to their student clinicians.
Growth of Therapy Applications and Marketing
App development, for both Android- and iOS-based tablets, has exploded over the past 5 years. With regards to iPad/iPhone technology, an astonishing 2 million apps are available for free or purchase in the Apple App Store (Statistica, 2016). A search of the app listings from the online resource www.yappguru.com showed a total of 682 apps listed across the categories augmentative and alternative communication (AAC), articulation/phonology, language, cognition, dysphagia, and voice (YappGuru, n.d.). Additionally, the specialized AAC blog www.janefarrall.com (Jane Farrall Consulting, n.d.) lists more than 300 AAC apps, of which only a small proportion are cross-listed on yappguru.com, suggesting that yappguru.com is not an exhaustive list, and the number of speech-language-pathology-related apps may be closer to 1,000, if not more. Although this is promising for clinicians, the array of apps in the marketplace creates a clear obstacle for those who aim to employ tablet technology in a meaningful, clinically effective, and evidence-based manner.
Apps are available to support a wide variety of intervention goals for articulation, receptive and expressive language for children and adults, fluency, voice, swallowing, pre-literacy skills, and functional communication training. There is also a range of tools dedicated specifically to AAC. Apps may be structured as static electronic flashcards for language and articulation drills (e.g., ArtikPix), or they may offer auditory or visual feedback for articulation, fluency, and voice therapy (e.g., Speech4Good). Other apps offer templates to support sentence-building (e.g., Sentence Builder) and story-telling (e.g., Pictello). With a recent push for evidence-based practice, some developers include the wording “evidence-based” in their apps' descriptions. This may mean one of two things: that the effectiveness of the app has been evaluated via peer-reviewed research (e.g., Mark, Onaral, & Ayaz's, 2016, regarding Constant Therapy), or, more typically, that the app features are based on a published theory or model of speech/language learning (e.g., a general statement on evidence-based practice on the website of the app developer SmartyEars, see: http://smartyearsapps.com/evidence-based-practice/).
Apps can range in cost from free—including trial and lite versions—to several hundred dollars, with many common apps costing between $10 and $50. The low cost and quick access make apps good practical solutions for many clinicians. However, there are competing concerns in app implementation that exist in the clinical realm and are echoed in university settings. A recent analysis of iPad-based instruction in higher education settings suggested that faculty “do not have a structured, pedagogical approach to aligning [the technology's] use within academic programmes” (Nguyen, Barton, & Nguyen, 2015). In communicative sciences and disorders, clinical supervisors and faculty must learn about new technology side-by-side with student clinicians. When clinical faculty members are not familiar with relevant technology, they may not effectively support students in implementing the technology, nor appropriately suggest app-based intervention tools. Moreover, new technologies can be attractive to student clinicians who, without appropriate supervisor guidance, run the risk of placing too much emphasis on the technology rather than maintaining a client-centered focus. In speech-language pathology, this can result in excessive purchasing of inappropriate technologies, lack of skill generalization, and eventual technology abandonment if the selected technology does not match client needs and preferences; these are long-standing issues in AAC that have become more broadly relevant with development of a wider range of intervention apps. To avoid both extremes, students and faculty need structured educational opportunities ranging from explicit instruction to guided exploration of relevant technologies.
Evidence-Based Practice in Intervention Technology
The American Speech-Language-Hearing Association (ASHA) presents a set of guidelines on its website for evaluating “any new procedure, product or program,” with respect to mobile apps (ASHA, n.d.). These guidelines include, among others, the questions: “To which population does the product apply? Are outcomes clearly stated? Is promotional material the only available published information?” and, specifically for apps, “How long will I be able to use it?” Several key questions from this list are typically not addressed by app developers. Most notably, while ASHA suggests checking for publications/peer-reviewed research about any new products, this information is often not available for intervention apps. Individual app features and whole applications have been closely evaluated in some areas of communicative disorders, including aphasia intervention (e.g., Stark & Warburton, 2016) and AAC applications (e.g., Beukelman, Hux, Dietz, McKelvey, & Weissling, 2015). However, the majority of apps that support intervention are not evaluated in peer-reviewed publications before they are released on the market, though there are several parent-run blogs (e.g., http://blog.momswithapps.com/) and professional-run websites (e.g., www.janefarrall.com) dedicated to app review. ASHA also provides other resources for app review at www.asha.org/SLP/schools/Applications-for-Speech-Language-Pathology-Practice/.
The lack of peer review is due in part to the recency of the field, and in part to limited incentive to conduct rigorous peer review of low-cost products. Motivation to conduct research on apps is low, likely because the cost of running a study is high and customers, including families and professionals, are most familiar with the “app store” model where purchase decisions are based on usability reviews from previous customers, rather than professional assessment. The fast turnover rate of the app market also motivates developers to launch applications as quickly as possible. For many apps, peer-reviewed research may not seem necessary; these technologies are frequently similar to printed materials already in use, and/or function as a small component of traditional interventions. Though evidence-based practice does not require availability of Level-I studies (i.e., controlled, blinded, large cohort, and experimental/control groups) (Dollaghan, 2007), it does require systematic critical approaches based on best available evidence (Dollaghan, 2004). Discussing the need to navigate a rapidly changing intervention field, Bernstein Ratner (2011)  suggests that, when faced with interventions that have a limited evidence base, clinicians can “employ, and then evaluate the outcomes of, new approaches” (p. 77). This piece of advice is especially relevant to the burgeoning field of intervention apps and needs to be taught to student clinicians as part of critical thinking instruction.
Push for Teaching Critical Thinking During Clinical Training
In pre-service learning, there has been a recent focus on developing critical thinking skills (Finn, Brundage, & DiLollo, 2016). Critical thinking has been defined as “thinking that is based on the principles of rationality” and, more pragmatically, “a set of skills that people can learn and apply in their everyday or professional lives” (Finn, 2011, p. 69). To teach critical thinking, Finn et al. (2016)  suggest specific strategies (citing Halpern, 2014), including “encouraging students' disposition or attitude toward effortful thinking and learning” and “directing learning activities in ways that increase the probability of trans-contextual transfer” (p. 49). They also suggest that “the strongest effects [on critical thinking] occurred when critical thinking was taught explicitly within content-specific courses, and active learning approaches were used that included class discussion, applied problem solving, and student mentoring (e.g., teacher-student interaction)” (Finn et al., 2016, p. 58). To that end, if we want our students to be critical consumers of new technologies, we need to model and scaffold these approaches while students are still in training, as well as offer opportunities for students to practice these approaches under faculty guidance.
Current Study
Describing current practice is an important component of EBP in communicative sciences and disorders (e.g., Lund, Wendy, Weissling, McKelvey, & Dietz, 2017; Thistle & Wilkinson, 2015). It uncovers existing practice patterns, highlights successful strategies, and demonstrates ways in which clinical practice is or is not aligned with research findings. The purpose of the current article is two-fold. First, we report on our approach to creating a systematic technology training program in our university's speech-language pathology clinic, including guidelines for intervention app selection, direct student training, unstructured device/app exploration (i.e., “assistive technology (AT) open house”), and use of student feedback. Second, we report on the results of a survey that assessed common methods of app selection, technology use, and student training at other university clinical training programs around the country (see Appendix A for details). Through the creation and dissemination of two surveys, we sought to specifically answer the following questions:
  • What factors impact student use of iPad apps?

  • How do we create a systematic approach to app selection and student training?

  • How do other professionals in our field approach app selection and student training?

Methods
A two-phased approach, approved by the university's Institutional Review Board, was implemented to measure trends in technology use by speech-language clinicians.
The Surveys
Phase 1 consisted of two parts, the first of which involved two surveys (pre-training and post-training) assessing student clinicians' knowledge, attitudes, and beliefs about using iPad technology in their university clinical setting, with a training module (described in more detail below) provided between each survey. The participants were a cohort of 21 graduate students beginning their initial clinical practicum at the on-campus clinic in a department of communication sciences and disorders. The purpose of the training module and surveys was to pilot and evaluate a systematic approach to tablet use in the clinic. The pre-training survey was optional and anonymous, provided to students after receiving their client assignments for the academic quarter. Twenty-one students (the full cohort of beginning clinicians) were administered the survey. Although the survey was optional, the response rate was 100% for the initial and 77% for the final survey.
The pre-training survey assessed the following:
  • knowledge of the technology available to students during clinical practicum,

  • knowledge of procedural access to available technology during clinical practicum,

  • knowledge of available clinic technology support during clinical practicum,

  • operational competence and confidence using an iPad in clinical practicum,

  • knowledge of all available clinic AAC-specific technology, and

  • beliefs regarding the benefit of technology-specific training.

The Training
The two-part training module consisted of (1) a brief, formal tech orientation to the assistive technology (AT) lab and its related services, as well as (2) an AT “open house.” Immediately after pre-training surveys were collected, a 20-minute mandatory orientation was provided to the student cohort outlining the available technology in the clinic's AT Lab (e.g., iPads, speech-generating devices). The orientation also provided students with information and internet links for in-house technology support, device scheduling, and necessary procedures to access equipment during their 12-week clinical practicum. At the end of the orientation, the students received an invitation to attend two separate 2-hour open houses for the AT Lab. The AT open house provided students with a dedicated time and space to access any device, app, or software for the purposes of experimentation and planning for their assigned client. Because of the nature of an open house, there was no structured lesson plan or rubric for the open house sessions. The AT open house was suggested, but not required, for students, who used it on as-needed basis.
The AT lab coordinator (first author) was present at each of the open houses, and was experientially qualified to provide information about the iPad devices, their apps, and the other AAC devices housed in the department. Since assuming the role of AT Lab Coordinator, the first author was active in the development of lab protocols, procurement of new clinically-relevant and evidence-supported apps, development of a management system for a new fleet of iPads, and resources for improved student access to technology. During each open house, the coordinator was present to supervise open use of the devices; offer troubleshooting advice; advise on types of apps available for different clinical populations, the request process for special requests for app installations, and the iPad reservation process; and provide instruction on adjusting system settings (e.g., guided access).
During the orientation and the open houses, students were also introduced to the clinic's request process that allows for new apps to be purchased and downloaded by the clinic. The app request process offered a systematic way to harness the knowledge of the digital-native generation and scaffold student understanding of important app features. Our process included an app evaluation rubric (adapted from Walker, 2013), with an array of scoring parameters (e.g., “degree to which skill(s) reinforced are connected to the targeted skill or concept” and “degree of flexibility an app offers in altering settings to meet student needs”). Students were required to submit a completed rubric along with a questionnaire which encouraged them to evaluate client goals and existing apps (see Figure 1).
Figure 1.

iPad App Request - Student Questionnaire. Permission to use the graphic in Figure 1 obtained by the Department of Communicative Sciences and Disorders, California State University, East Bay.

 iPad App Request - Student Questionnaire. Permission to use the graphic in Figure 1 obtained by the Department of Communicative Sciences and Disorders, California State University, East Bay.
Figure 1.

iPad App Request - Student Questionnaire. Permission to use the graphic in Figure 1 obtained by the Department of Communicative Sciences and Disorders, California State University, East Bay.

×
At the completion of the cohort's clinical practicum, a link to the online post-training survey was emailed to each of the 21 members of the original student cohort. The post-training survey was also anonymized and optional, addressing identical items as the pre-training survey, with the addition of a novel question assessing the students' perceived benefit of the tech training and AT open houses, as well as student barriers to accessing available technology during their clinical practicum.
Technology Usage Surveillance
The second part of Phase 1 was designed to objectively measure usage trends for available clinical technology by monitoring device check-out logs that indicated date, time, device, and specific app/software used by the student clinicians. The department mandated that students complete an entry in the check-out log as part of the student user-agreement for clinic technology. The purpose of monitoring the check-out logs after the training module was to identify whether app usage increased from the prior quarter. A copy of each log was retained and each iPad's app use was tallied. All non-tablet related check-outs were tallied separately, as the bulk of technology use in the clinic were iPads.
Assessing Clinical Technology Training in Higher Education
Phase 2 consisted of a survey disseminated to members of ASHA's Special Interest Group 10, Issues in Higher Education, to better understand the ways other clinical training programs approach decision-making processes for technology appraisal and student training in its use. The survey was disseminated to members via the SIG's message board, which provided a link to an online survey. A copy of the survey can be found in Appendix A. The survey was anonymized and provided a 3-month window for members to submit the survey. Three reminder emails were provided before the survey was closed for submission. The survey assessed the following:
  • the respondent's institutional position (e.g., faculty, clinical staff, student);

  • typical clinical setting (e.g., hospital, onsite clinic);

  • estimated annual clinic caseload;

  • number of student clinicians per academic term;

  • number of tablets (iOS/Android/other) available for clinic;

  • estimated device usage, quantified by tablet type;

  • available uses for tablet technology in clinic (e.g., therapy, AAC, motivation/rewards);

  • training provided to students, faculty, and/or staff regarding clinical tablet use; and

  • clinical decision-making structure for app purchase.

Results
Student Outcomes with Direct Training
During Phase 1, 21 students completed the pre-training survey preceding the tech orientation and open houses, though some elected to only answer certain questions. The results from the pre-training survey are displayed in Table 1.
Table 1. Pre-Training Student Cohort Survey
Pre-Training Student Cohort Survey×
Survey Question Strongly Agree Agree Unsure Disagree Strongly Disagree n=
1. I know what technological devices are available to me during my clinical practicum. 1 3 7 4 5 20
(5.0%) (15.0%) (35.0%) (20.0%) (25.0%)
2. I know how to access and get assistance with equipment in the AT Lab. 0 0 7 (36.8%) 5 7 19
(0%) (0%) (26.4%) (36.8%)
3. I know how to operate an iPad, manage its user settings, and navigate its apps. 5 8 4 0 3 20
(25.0%) (40.0%) (20. 0%) (0%) (15.0%)
4. In addition to iPads, I am aware of the types of equipment available for AAC clients. 0 2 8 4 5 19
(0%) (10.5%) (42.1%) (21.1%) (26.3%)
5. I can incorporate an iPad into a therapy session in an effective, relevant manner. 2 8 4 2 2 18
(11.1%) (44.5%) (22.2%) (11.1%) (11.1%)
6. I am confident in my ability to use iPad technology during a therapy session. 3 6 4 3 3 19
(15.8%) (31.6%) (21.0%) (15.8%) (15.8%)
7. (a) I feel some training would increase my willingness to use iPads during my clinical practicum. 13 8 0 0 0 21
(61.9%) (38.1%) (0%) (0%) (0%)
Table 1. Pre-Training Student Cohort Survey
Pre-Training Student Cohort Survey×
Survey Question Strongly Agree Agree Unsure Disagree Strongly Disagree n=
1. I know what technological devices are available to me during my clinical practicum. 1 3 7 4 5 20
(5.0%) (15.0%) (35.0%) (20.0%) (25.0%)
2. I know how to access and get assistance with equipment in the AT Lab. 0 0 7 (36.8%) 5 7 19
(0%) (0%) (26.4%) (36.8%)
3. I know how to operate an iPad, manage its user settings, and navigate its apps. 5 8 4 0 3 20
(25.0%) (40.0%) (20. 0%) (0%) (15.0%)
4. In addition to iPads, I am aware of the types of equipment available for AAC clients. 0 2 8 4 5 19
(0%) (10.5%) (42.1%) (21.1%) (26.3%)
5. I can incorporate an iPad into a therapy session in an effective, relevant manner. 2 8 4 2 2 18
(11.1%) (44.5%) (22.2%) (11.1%) (11.1%)
6. I am confident in my ability to use iPad technology during a therapy session. 3 6 4 3 3 19
(15.8%) (31.6%) (21.0%) (15.8%) (15.8%)
7. (a) I feel some training would increase my willingness to use iPads during my clinical practicum. 13 8 0 0 0 21
(61.9%) (38.1%) (0%) (0%) (0%)
×
The post-training survey was conducted following the completion of the cohort's quarter-long clinical practicum. Five of the 21 original participants were lost to attrition (24%), with 16 students submitting the post-training survey. The results from the follow-up survey are displayed in Table 2.
Table 2. Post-Training Student Cohort Survey
Post-Training Student Cohort Survey×
Survey Question Strongly Agree Agree Unsure Disagree Strongly Disagree n =
1. I know what technological devices are available to me during my clinical practicum. 2 8 3 2 1 16
(12.5%) (50.0%) (18.8%) (12.5%) (6.2%)
2. I know how to access and get assistance with equipment in the AT Lab. 2 7 4 3 0 16
(12.4%) (43.8%) (25.0%) (18.8%) (0%)
3. I know how to operate an iPad, manage its user settings, and navigate its apps. 2 7 3 3 1 16
(12.4%) (43.8%) (18.8%) (18.8%) (6.2%)
4. In addition to iPads, I am aware of the types of equipment available for AAC clients. 0 0 6 8 2 16
(0%) (0%) (37.5%) (50.0%) (12.5%)
5. I can incorporate an iPad into a therapy session in an effective, relevant manner. 0 6 7 0 3 16
(0%) (37.4%) (43.8%) (0%) (18.8%)
6. I am confident in my ability to use iPad technology during a therapy session. 0 5 5 3 3 16
(0%) (31.3%) (31.3%) (18.7%) (18.7%)
7. (b) The Lab orientation I received increased my willingness to use iPads during my clinical practicum. 1 5 7 3 0 16
(6.3%) (31.3%) (43.7%) (18.7%) (0%)
Table 2. Post-Training Student Cohort Survey
Post-Training Student Cohort Survey×
Survey Question Strongly Agree Agree Unsure Disagree Strongly Disagree n =
1. I know what technological devices are available to me during my clinical practicum. 2 8 3 2 1 16
(12.5%) (50.0%) (18.8%) (12.5%) (6.2%)
2. I know how to access and get assistance with equipment in the AT Lab. 2 7 4 3 0 16
(12.4%) (43.8%) (25.0%) (18.8%) (0%)
3. I know how to operate an iPad, manage its user settings, and navigate its apps. 2 7 3 3 1 16
(12.4%) (43.8%) (18.8%) (18.8%) (6.2%)
4. In addition to iPads, I am aware of the types of equipment available for AAC clients. 0 0 6 8 2 16
(0%) (0%) (37.5%) (50.0%) (12.5%)
5. I can incorporate an iPad into a therapy session in an effective, relevant manner. 0 6 7 0 3 16
(0%) (37.4%) (43.8%) (0%) (18.8%)
6. I am confident in my ability to use iPad technology during a therapy session. 0 5 5 3 3 16
(0%) (31.3%) (31.3%) (18.7%) (18.7%)
7. (b) The Lab orientation I received increased my willingness to use iPads during my clinical practicum. 1 5 7 3 0 16
(6.3%) (31.3%) (43.7%) (18.7%) (0%)
×
Differences in the pre- and post-training responses to Questions 1 & 2 allow us to suggest that the initial training helped students with clinic-specific aspects of technology use (knowing what technology and supports are available to them in the clinic); however, the remaining survey question responses were mixed. As expected, most respondents initially agreed that training would positively improve their attitudes about using iPads in clinical scenarios, yet less than half of respondents agreed that the orientation and training accomplished their goals.
Technology Usage Trends
The second part of Phase 1 revealed a 170% increase in iPad check-outs, growing from 43 documented check-outs during the previous quarter to 116 check-outs during the first quarter the training was offered. The check-out log also revealed that AAC-related apps were the ones most commonly used, with students more frequently checking out high-tech speech-generating apps (e.g., Proloquo2Go) versus simpler and less configurable options (e.g., the Lingraphica Small Talk series). Students also preferred apps that typically allowed implementation of multiple goals in a session (e.g., Constant Therapy) or those that provided interactive visual feedback for a variety of pediatric language and articulation goals (e.g., Speech with Milo and Speech Tutor). Interestingly, student clinicians favored the ability to individualize stimulus materials using the Quizlet app, rather than using pre-programed stimuli packages such as those found in other goal-specific apps (e.g., ArtikPix).
Trends in Higher Education Technology Training
The Phase 2 survey disseminated to ASHA's SIG 10 received 35 responses, of which 54% reported to be full-time faculty. There are several hundred speech-language pathology training programs in the United States, so the survey results represent only a small selection of programs and must be treated as pilot data. Of the respondents, nearly 83% reported their clinical setting to be an onsite university speech-language-hearing clinic. More than 60% of the respondents reported that their clinic provided services to an annual caseload of 75+ clients/patients. Most clinical settings provided between 1 and 15 tablets, with iPad being the most commonly employed technology. Android-based tablets and touchscreen laptops (e.g., Lingraphica) were much less commonly used. Table 3 indicates the clinical purposes for which tablet technology was commonly employed.
Table 3. App Use as Related to Disorder among Clinical Training Programs
App Use as Related to Disorder among Clinical Training Programs×
Clinical AAC Pediatric Language Games Pediatric Speech SLP Ed & Training Adult Speech
Application
# of Responses 31 30 30 29 24 24
% of Responses 88.6% 85.7% 85.7% 82.8% 68.6% 68.6%
Clinical Adult Language Pragmatic Skills Pediatric Literacy Counseling Cognitive Tx Pediatric Dx
Application
# of Responses 23 22 20 14 14 13
% of Responses 65.7% 62.9% 57.1% 40.0% 40.0% 37.1%
Clinical Adult Literacy Fluency Adult Voice Social Networks Dysphagia
Application
Dx
# of Responses 13 13 11 9 8 2
% of Responses 37.1% 37.1% 31.4% 25.7% 22.8% 5.7%
Table 3. App Use as Related to Disorder among Clinical Training Programs
App Use as Related to Disorder among Clinical Training Programs×
Clinical AAC Pediatric Language Games Pediatric Speech SLP Ed & Training Adult Speech
Application
# of Responses 31 30 30 29 24 24
% of Responses 88.6% 85.7% 85.7% 82.8% 68.6% 68.6%
Clinical Adult Language Pragmatic Skills Pediatric Literacy Counseling Cognitive Tx Pediatric Dx
Application
# of Responses 23 22 20 14 14 13
% of Responses 65.7% 62.9% 57.1% 40.0% 40.0% 37.1%
Clinical Adult Literacy Fluency Adult Voice Social Networks Dysphagia
Application
Dx
# of Responses 13 13 11 9 8 2
% of Responses 37.1% 37.1% 31.4% 25.7% 22.8% 5.7%
×
Most responses indicated that the decision-making process is based on word-of-mouth recommendations from faculty/staff, students, and clients (72% of responses), whereas only 9.4% of responses indicated the use of a systematic app review process/rubric to appraise an app prior to its procurement. Finally, approaches to technology training across clinics varied greatly, with 29% electing a direct training approach and 61% electing an indirect or as-needed approach.
Discussion
This preliminary study addressed two issues related to technology use within university clinics: factors that impact student clinician uses of iPad apps and systematic approaches to app implementation, within our clinic and other university clinics.
Factors That Impact Student Use of iPad Apps
In our university clinic, use of intervention apps markedly increased after a two-part training module was provided to students. Though some of this was possibly due to a slight increase in clinic enrollment and the types of clinical services being provided to each client in a particular quarter (e.g., AAC, aphasia therapy, pediatric articulation therapy), the surveyed clinicians also reported feeling much more comfortable with clinic-specific procedures for technology check-out and getting assistance. There is the possibility that the position of the first author as the AT Lab Coordinator during this time may have positively influenced members of his cohort to more readily use iPads in their clinical practicum. Students did not, however, report feeling more confident in overall clinical iPad use after the initial training. In fact, students reported feeling less confident about whether or not they could implement an iPad effectively within a therapy session (Questions 5 & 6). Because these were first-time student clinicians, it is possible that they were not ready to choose and explore client-relevant apps in time for the AT open house. It is also possible that—although students initially felt comfortable navigating iPads for personal use—once they learned about the variety of available clinical applications, their view of their own abilities began to reflect clinical skills, rather than personal use competencies. Nascent clinicians may need more structured training in app selection, suggesting that clinics should take an active approach in ensuring that either (1) clinical supervisors can confidently demonstrate intervention skills to their students using tablet technology on a one-to-one basis, and/or (2) a resource is made available specifically for students to access technology-related assistance as it relates to clinical intervention (e.g., an AT Lab Coordinator and in-house resources).
Based in part on survey results, we have implemented a more formal “app introduction” process in our clinic, with the AT Lab Coordinator (who is always a student in the department's graduate program) explicitly introducing new technologies to clinicians in subsequent quarters following the conclusion of this study. Recently, more clinicians have informally reported taking advantage of the AT open house. Although we acknowledge that the post-training survey results were mixed in regard to student attitudes and confidence in using iPad technology to implement speech-language therapy, the sizeable increase in usage suggests that the training and open house result in increased student interest. Based on informal data collected in 2016, the increase in use of apps in intervention has been maintained.
These results are promising from both an educational and financial perspective as increased use justifies financial investment in clinical technology. Additionally, our clinic now has what we believe to be effective procedures in place that require students to match the app to a client goal when using existing technology, and use a clinical rubric to evaluate new apps. App tracking through auditing check-out logs has helped us to identify which apps were most and least useful to students. This allows us to remove apps that are infrequently used and identify which apps offer the greatest benefit to our student clinicians and their clients. Further, our app monitoring reflects which types of client populations are most frequently receiving iPad-supported therapy interventions. In our clinic, we find that apps supporting AAC with speech-generating capacity, visual-feedback/demonstration for articulation therapy, and interactive pediatric language apps are most frequently employed, with far fewer uses when addressing voice or literacy goals. Like our clinic's trends, other universities report that most of their apps are specific to AAC and various speech-language goals. Understanding usage data plays a crucial role in our AT Lab Coordinator's ability to plan the layout for our fleet of iPads, which we separate into adult-customization and pediatric-customization to maximize our devices' memory (storage) constraints and help allocate devices for multiple clinic schedules.
Though we have a system in place for students to request new applications, we have not seen an increase in student requests for new apps, which average one or less per quarter. This could mean that student clinicians have the apps they need and/or are not willing to go through the request process. We have also observed that student clinicians occasionally choose to bring in personal devices with privately purchased apps. This presents a range of challenges for clinics, including the potential for patient privacy violations and liability for device damage.
Developing a Systematic Approach to Technology Training
The results of our professional survey suggest that pedagogical practices related to technology generally vary among university settings, and are likely to be dependent on each specific clinic's resources and student needs. In our clinical setting, we believe a direct student-training style supplemented with hands-on practice to be most beneficial. While the results from our 2015 post-training student survey were mixed, students have since anecdotally reported finding benefit in having the following available to them throughout their clinical practicum:
  • A dedicated clinic staff member with weekly availability for technology consultation and troubleshooting (i.e., AT Lab Coordinator).

  • Online resources that outline available technology, apps, and procedures for getting technology support throughout the clinical practicum.

  • A semi-structured orientation and subsequent open house access in which hands-on learning is encouraged and supported.

In other settings, if students have experience using an iPad for numerous purposes, this might argue for the adoption of a more hands-off approach (i.e., as-needed consultations with a clinical supervisor or independent research). In our setting, a more direct approach seemed to best fulfil student needs and showed measurable increases in tablet and varied app use.
Considering the cost associated with the purchase of many speech-language therapy apps and the tablets on which they operate, clinical training programs should be motivated to ensure that purchased technologies have a high benefit-cost ratio. Tracking device/app use can help university clinics (1) learn whether apps provided to clinicians closely reflect the composition of a clinic's client population and (2) eliminate app redundancy when appropriate. When there are many apps from which to choose and training isn't provided in the nuances and clinical benefits of each, the risk of abandonment is high. In fact, a recent article reported, “the percentage of users who abandon an app after one use is now 23%, a slight improvement from the 25% we saw in 2015” (O'Connell, 2016, para. 2). Because app abandonment, particularly in our field, can result in a markedly reduced benefit-cost ratio for clinic technology investments, it is well-worth the energy to ensure that technology is utilized to its fullest extent.
App abandonment also raises the question of client/patient compliance with clinical interventions. There is all too frequently a mismatch between the technology and the client/patient's needs, values, and personal preferences, yielding reduced or poor compliance with some or all aspects of the chosen intervention. In university training programs, it is critical that student clinicians consider client characteristics and preferences when deciding on an app-based intervention. By implementing strategies such as feature-matching and app review rubrics, programs can support students in designing interventions based on the principles of client-centered therapy, which, in turn, will maximize client/patient compliance.
We suggest, based on student survey results and monitoring of device usage, that students are more likely to seek out opportunities to use apps provided they are given adequate training and time to practice—such as in an open house. We also believe that this happens best in a direct-training and hands-on guided practice model (i.e., an orientation provided to all students and subsequent opportunities for open houses). To make our AT system work, our clinic now routinely staffs a part-time student employee to assist an overseeing faculty member conduct these trainings. To bolster the sustainability of our clinic's technology program, the AT Lab Coordinator at the time of this study developed and piloted a series of systems to run the lab, including a mobile management server with associated app volume purchase program, an online help-desk for staff and students, a web-based working app inventory, and a training manual for future AT Lab Coordinators.
EBP in Selecting and Implementing Technology
There are tools available that support systematic evaluation of a clinical app on various parameters before purchase (Walker, 2013). However, our professional survey suggests that app decisions are more commonly made on a variety of recommendations. This mirrors our profession's overall tendency to make clinical decisions based primarily on information received from our colleagues via word-of-mouth (Bernstein Ratner, 2006). As a profession, however, we need to be aware of the dilemma this presents as we are increasingly required to base our clinical decision-making on more robust evidence.
Apps are designed by clinicians, researchers, and laypersons alike. Therefore, it is contingent upon speech-language professionals to effectively evaluate the products (i.e., apps) they purchase. Although this may be of lesser importance for apps designed for motivation/game purposes, others that address as specific speech-language skill should be assessed as rigorously as any other treatment procedure (e.g., naming therapy for anomic aphasia). There have been interventions and materials in speech-language pathology that were very popular with clinicians, but were found to be ineffective after rigorous investigation (e.g., non-speech oral motor exercises as discussed by Lass & Pannbacker, 2008). It is essential, therefore, for our profession to seek methods of critical appraisal. In our clinic, we have recently instituted a more rigorous process of app procurement. When student or staff member requests an app for purchase or free download, they are required to complete an app evaluation rubric and submit a formal request form in which they must identify a client-specific rationale and proof that the app provides a function not currently met by another related app. It is important to note that an app evaluation rubric does not substitute for peer-reviewed intervention research. However, in the absence of an empirical basis for app selection, the app selection process and rubric minimizes redundant app purchases and instills a process of systematic evaluation to ensure that evidence-based practice is fluidly intertwined throughout the clinical training experience.
Future Directions
In future academic terms, we will transition the student survey entirely online and explore the option of making it a required component of a clinical preparation course. This should provide more complete data and increase early student awareness of technology-related clinical skill development. Also, increasing student awareness regarding the benefit of completing the survey may increase student motivation (i.e., it allows for more focused training to students' needs and for a more tailored training experience for student clinicians). Other future directions for our clinic involve (1) systematizing clinical supervisor training so that they can quickly and effectively learn about our available technology, and (2) collecting data on which of our existing apps are used most frequently and on reported gaps in relevant technology. Last, we want to continue to survey members of ASHA's Special Interest Group 10 to stay abreast of changing trends among speech-language pathology training programs regarding how their technology implementation practices are evolving over time.
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Appendix A.
Higher Education Technology Survey
1. What is your institutional position? (select one)
  • Administrator (full-time)

  • Administrator (part-time)

  • Academic faculty (full-time)

  • Academic faculty (part-time)

  • Clinical supervisor (full-time)

  • Clinical supervisor (part-time)

  • Doctoral/graduate student

  • Other (please specify below)

2. What is your typical institutional clinical setting? (select all that apply)
  • Onsite speech-language clinic

  • Offsite speech-language clinic

  • Onsite medical center

  • Offsite medical center

  • Private practice

  • Home visits (client's/patient's home)

  • Other (please specify below)

3. Approximately how many total clients/patients are served in your clinical setting annually for both diagnostic and treatment purposes? (select one)
  • 0-25 clients/patients

  • 25-50 clients/patients

  • 50-75 clients/patients

  • 75-100 clients/patients

  • Unknown

  • This question does not apply to me

  • Other (please specify below)

4. In a typical academic term (e.g., quarter/semester), approximately how many student clinicians complete a clinical practicum? (select one)
  • 0-15 student clinicians

  • 15-30 student clinicians

  • 30-45 student clinicians

  • 45-60 student clinicians

  • 60-75 student clinicians

  • More than 75 student clinicians

  • This question does not apply to me

  • Other (please specify below)

5. In my clinical setting, clinicians have regular access to the following types of tablet technology for clinical diagnostics or intervention. (select all that apply and estimate the quantity of each device available)
1-5 devices 5-10 devices 10-15 devices 15-25 devices 25-35 devices 35-50 devices 50 + devices Cannot answer
iPad
Android
Tablets
Other
Describe “other” here:
1-5 devices 5-10 devices 10-15 devices 15-25 devices 25-35 devices 35-50 devices 50 + devices Cannot answer
iPad
Android
Tablets
Other
Describe “other” here:
×
6. Please identify all possible uses for the tablet devices available in your clinical setting. (select all that apply)
  • This question does not apply to me

  • Student education/clinical training

  • Client/patient/family counseling

  • AAC

  • Pediatric diagnostics

  • Pediatric speech

  • Pediatric language

  • Pediatric literacy

  • Adult diagnostics

  • Adults speech

  • Adults language

  • Adult/Adolescent literacy

  • Social networking

  • Motivators/games

  • Social language/pragmatics

  • Cognitive intervention

  • Dysphagia

  • Voice Fluency

  • Other (please specify below)

7. What types of training/education about the clinical use of iPads/tablets are provided to your department's SLP/Aud students, clinical supervisors, and academic faculty? (select all that apply)
  • Direct training/education situations (e.g., coursework, formal orientations/training)

  • Indirect training/education situations (e.g., manuals or resources provided)

  • As-needed training/education by designated staff person (e.g., office hours, help desk)

  • This question does not apply to me

  • Other (please specify below)

8. Please choose the decision-making processes for requesting/downloading/purchasing a device or app within your clinical setting. (select all that apply)
  • App evaluation rubric

  • Faculty/staff recommendation

  • Student recommendation

  • Client/patient recommendation

  • Recommendation from trusted web-sources (please list source(s) in comment section below)

  • Developer promotion/free trials

  • Word-of-mouth

  • This question does not apply to me

  • Other (please describe in the comment section below)

Appendix B.
Mobile Applications Mentioned in this Article
Inclusion of an application on this list does not constitute endorsement by the authors. Readers are encouraged to explore applications and consider the app characteristics listed in the article to help clients make decisions about app selection.
Figure 1.

iPad App Request - Student Questionnaire. Permission to use the graphic in Figure 1 obtained by the Department of Communicative Sciences and Disorders, California State University, East Bay.

 iPad App Request - Student Questionnaire. Permission to use the graphic in Figure 1 obtained by the Department of Communicative Sciences and Disorders, California State University, East Bay.
Figure 1.

iPad App Request - Student Questionnaire. Permission to use the graphic in Figure 1 obtained by the Department of Communicative Sciences and Disorders, California State University, East Bay.

×
Table 1. Pre-Training Student Cohort Survey
Pre-Training Student Cohort Survey×
Survey Question Strongly Agree Agree Unsure Disagree Strongly Disagree n=
1. I know what technological devices are available to me during my clinical practicum. 1 3 7 4 5 20
(5.0%) (15.0%) (35.0%) (20.0%) (25.0%)
2. I know how to access and get assistance with equipment in the AT Lab. 0 0 7 (36.8%) 5 7 19
(0%) (0%) (26.4%) (36.8%)
3. I know how to operate an iPad, manage its user settings, and navigate its apps. 5 8 4 0 3 20
(25.0%) (40.0%) (20. 0%) (0%) (15.0%)
4. In addition to iPads, I am aware of the types of equipment available for AAC clients. 0 2 8 4 5 19
(0%) (10.5%) (42.1%) (21.1%) (26.3%)
5. I can incorporate an iPad into a therapy session in an effective, relevant manner. 2 8 4 2 2 18
(11.1%) (44.5%) (22.2%) (11.1%) (11.1%)
6. I am confident in my ability to use iPad technology during a therapy session. 3 6 4 3 3 19
(15.8%) (31.6%) (21.0%) (15.8%) (15.8%)
7. (a) I feel some training would increase my willingness to use iPads during my clinical practicum. 13 8 0 0 0 21
(61.9%) (38.1%) (0%) (0%) (0%)
Table 1. Pre-Training Student Cohort Survey
Pre-Training Student Cohort Survey×
Survey Question Strongly Agree Agree Unsure Disagree Strongly Disagree n=
1. I know what technological devices are available to me during my clinical practicum. 1 3 7 4 5 20
(5.0%) (15.0%) (35.0%) (20.0%) (25.0%)
2. I know how to access and get assistance with equipment in the AT Lab. 0 0 7 (36.8%) 5 7 19
(0%) (0%) (26.4%) (36.8%)
3. I know how to operate an iPad, manage its user settings, and navigate its apps. 5 8 4 0 3 20
(25.0%) (40.0%) (20. 0%) (0%) (15.0%)
4. In addition to iPads, I am aware of the types of equipment available for AAC clients. 0 2 8 4 5 19
(0%) (10.5%) (42.1%) (21.1%) (26.3%)
5. I can incorporate an iPad into a therapy session in an effective, relevant manner. 2 8 4 2 2 18
(11.1%) (44.5%) (22.2%) (11.1%) (11.1%)
6. I am confident in my ability to use iPad technology during a therapy session. 3 6 4 3 3 19
(15.8%) (31.6%) (21.0%) (15.8%) (15.8%)
7. (a) I feel some training would increase my willingness to use iPads during my clinical practicum. 13 8 0 0 0 21
(61.9%) (38.1%) (0%) (0%) (0%)
×
Table 2. Post-Training Student Cohort Survey
Post-Training Student Cohort Survey×
Survey Question Strongly Agree Agree Unsure Disagree Strongly Disagree n =
1. I know what technological devices are available to me during my clinical practicum. 2 8 3 2 1 16
(12.5%) (50.0%) (18.8%) (12.5%) (6.2%)
2. I know how to access and get assistance with equipment in the AT Lab. 2 7 4 3 0 16
(12.4%) (43.8%) (25.0%) (18.8%) (0%)
3. I know how to operate an iPad, manage its user settings, and navigate its apps. 2 7 3 3 1 16
(12.4%) (43.8%) (18.8%) (18.8%) (6.2%)
4. In addition to iPads, I am aware of the types of equipment available for AAC clients. 0 0 6 8 2 16
(0%) (0%) (37.5%) (50.0%) (12.5%)
5. I can incorporate an iPad into a therapy session in an effective, relevant manner. 0 6 7 0 3 16
(0%) (37.4%) (43.8%) (0%) (18.8%)
6. I am confident in my ability to use iPad technology during a therapy session. 0 5 5 3 3 16
(0%) (31.3%) (31.3%) (18.7%) (18.7%)
7. (b) The Lab orientation I received increased my willingness to use iPads during my clinical practicum. 1 5 7 3 0 16
(6.3%) (31.3%) (43.7%) (18.7%) (0%)
Table 2. Post-Training Student Cohort Survey
Post-Training Student Cohort Survey×
Survey Question Strongly Agree Agree Unsure Disagree Strongly Disagree n =
1. I know what technological devices are available to me during my clinical practicum. 2 8 3 2 1 16
(12.5%) (50.0%) (18.8%) (12.5%) (6.2%)
2. I know how to access and get assistance with equipment in the AT Lab. 2 7 4 3 0 16
(12.4%) (43.8%) (25.0%) (18.8%) (0%)
3. I know how to operate an iPad, manage its user settings, and navigate its apps. 2 7 3 3 1 16
(12.4%) (43.8%) (18.8%) (18.8%) (6.2%)
4. In addition to iPads, I am aware of the types of equipment available for AAC clients. 0 0 6 8 2 16
(0%) (0%) (37.5%) (50.0%) (12.5%)
5. I can incorporate an iPad into a therapy session in an effective, relevant manner. 0 6 7 0 3 16
(0%) (37.4%) (43.8%) (0%) (18.8%)
6. I am confident in my ability to use iPad technology during a therapy session. 0 5 5 3 3 16
(0%) (31.3%) (31.3%) (18.7%) (18.7%)
7. (b) The Lab orientation I received increased my willingness to use iPads during my clinical practicum. 1 5 7 3 0 16
(6.3%) (31.3%) (43.7%) (18.7%) (0%)
×
Table 3. App Use as Related to Disorder among Clinical Training Programs
App Use as Related to Disorder among Clinical Training Programs×
Clinical AAC Pediatric Language Games Pediatric Speech SLP Ed & Training Adult Speech
Application
# of Responses 31 30 30 29 24 24
% of Responses 88.6% 85.7% 85.7% 82.8% 68.6% 68.6%
Clinical Adult Language Pragmatic Skills Pediatric Literacy Counseling Cognitive Tx Pediatric Dx
Application
# of Responses 23 22 20 14 14 13
% of Responses 65.7% 62.9% 57.1% 40.0% 40.0% 37.1%
Clinical Adult Literacy Fluency Adult Voice Social Networks Dysphagia
Application
Dx
# of Responses 13 13 11 9 8 2
% of Responses 37.1% 37.1% 31.4% 25.7% 22.8% 5.7%
Table 3. App Use as Related to Disorder among Clinical Training Programs
App Use as Related to Disorder among Clinical Training Programs×
Clinical AAC Pediatric Language Games Pediatric Speech SLP Ed & Training Adult Speech
Application
# of Responses 31 30 30 29 24 24
% of Responses 88.6% 85.7% 85.7% 82.8% 68.6% 68.6%
Clinical Adult Language Pragmatic Skills Pediatric Literacy Counseling Cognitive Tx Pediatric Dx
Application
# of Responses 23 22 20 14 14 13
% of Responses 65.7% 62.9% 57.1% 40.0% 40.0% 37.1%
Clinical Adult Literacy Fluency Adult Voice Social Networks Dysphagia
Application
Dx
# of Responses 13 13 11 9 8 2
% of Responses 37.1% 37.1% 31.4% 25.7% 22.8% 5.7%
×
1-5 devices 5-10 devices 10-15 devices 15-25 devices 25-35 devices 35-50 devices 50 + devices Cannot answer
iPad
Android
Tablets
Other
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1-5 devices 5-10 devices 10-15 devices 15-25 devices 25-35 devices 35-50 devices 50 + devices Cannot answer
iPad
Android
Tablets
Other
Describe “other” here:
×
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